cpalgorithms
NumPy
cpalgorithms | NumPy | |
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1 | 272 | |
17 | 26,413 | |
- | 1.1% | |
0.0 | 10.0 | |
11 months ago | 3 days ago | |
C++ | Python | |
MIT License | GNU General Public License v3.0 or later |
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cpalgorithms
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Hacktoberfest: 69 Beginner-Friendly Projects You Can Contribute To
https://github.com/namanvats/cpalgorithms Algorithms and Techniques for competitive programming
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
cp-algorithms - Algorithm and data structure articles for https://cp-algorithms.com (based on http://e-maxx.ru)
SymPy - A computer algebra system written in pure Python
code_problems - Code Problems from Coding Challenge Websites. The goal is to help them to improve their code skills and also studying for coding interviews.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
JRuby - JRuby, an implementation of Ruby on the JVM
blaze - NumPy and Pandas interface to Big Data
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
SciPy - SciPy library main repository
pytest - The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
Numba - NumPy aware dynamic Python compiler using LLVM
Ansible - Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to cloud management, in a language that approaches plain English, using SSH, with no agents to install on remote systems. https://docs.ansible.com.
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).